science

Visible learning

Visible learning is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Visible learning rather than just read about it. In short: Visible learning is a meta-study that analyzes effect sizes of measurable influences on learning outcomes in educational settings. It was published by John Hattie in 2008 and draws upon results from 815 other meta-analyses.

Key takeaways

Visible learning belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Visible learning to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Visible learning from memory before moving on to harder problems.

Reference excerpt

Visible learning is a meta-study that analyzes effect sizes of measurable influences on learning outcomes in educational settings. It was published by John Hattie in 2008 and draws upon results from 815 other meta-analyses. The Times Educational Supplement described Hattie's meta-study as "teaching's holy grail". Hattie compared the effect sizes of influences on learning outcomes - in particular by using Cohen's d as a measure. He points out that in education most things work. The question is which strategies and innovations work best and where to concentrate efforts in order to improve student achievement. Hattie found that the aspects most correlated with student achievement were:

Self-reported grades (d=1.44): correlation between self-assessment and actual grades Piagetian programs (d=1.28): correlation between Piagetian stage and achievement Providing formative evaluation of programs (d=0.90) Microteaching (d=0.88) Acceleration (d=0.88) Classroom behavioral (d=0.80) Interventions for learning disabled students (d=0.77) Teacher clarity (d=0.75) Reciprocal teaching (d=0.74) Feedback (d=0.73) Teacher-student relationships (d=0.72) Spaced vs. mass practice (d=0.71) Meta-cognitive strategies (d=0.69) Prior achievement (d=0.67) Reading: vocabulary programs (d=0.67) Reading: repeated reading programs (d=0.67) Some of the statistical methods used by Hattie have been criticised. Hattie himself admitted that the values for the Common language effect size (CLE) in Visible Learning were calculated incorrectly throughout the book, with only the values for cohen's d being correct. In 2014, Rolf Schulmeister and Jörn Loviscach pointed out "considerable issues in terms of the selection of studies and the methods employed" in the meta analysis. Amongst others, they criticize the use of questionable or wrongly-categorized studies and misleading or nonsensical statistics. The phrase "visible learning" was used previously by Howard Gardner in his 2001 study "Making Learning Visible" as Inez De Florio argued in 2016.

References

External links Education: What works and what does not, with Professor John Hattie, Bridging the Gaps: A Portal for Curious Minds

Worked examples

Example 1 — a first encounter with Visible learning

Start with the simplest possible case. Write down what Visible learning claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Visible learning before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Visible learning ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Visible learning

In research: Visible learning appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Visible learning in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Visible learning is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2008 documents, Australian inventions, Learning, so understanding it makes those chapters shorter.
In everyday life: Look for Visible learning outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Visible learning in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Visible learning means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Visible learning out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Visible learning in simple terms?

Why does Visible learning matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Visible learning?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Visible learning.